Semantic matchmaking of assets to missions

Abstract

Some resources (i.e., assets) can be critical to accomplish missions. Unfortunately, in many settings these resources are limited. Scarcity of the critical assets and importance of the missions create an incentive for the organizations to cooperate by sharing their assets with an expectation of carrying out their missions successfully even if the assets in hand are limited. In this paper, we propose a multiagent framework where mission plans are semantically described so that a hierarchical multiagent system can be used to represent each mission. Using the semantic description of the mission plans, the agents reason about resources required for their missions and cooperatively decide on the assets that should be shared to carry out those missions. This is achieved at different levels of the agent hierarchy where policies and constraints are used during the decision process. Our experiments show that our approach leads to a better utilization of the assets and significantly improves the number of achievable missions when the number of available assets is limited.

abstract = "Some resources (i.e., assets) can be critical to accomplish missions. Unfortunately, in many settings these resources are limited. Scarcity of the critical assets and importance of the missions create an incentive for the organizations to cooperate by sharing their assets with an expectation of carrying out their missions successfully even if the assets in hand are limited. In this paper, we propose a multiagent framework where mission plans are semantically described so that a hierarchical multiagent system can be used to represent each mission. Using the semantic description of the mission plans, the agents reason about resources required for their missions and cooperatively decide on the assets that should be shared to carry out those missions. This is achieved at different levels of the agent hierarchy where policies and constraints are used during the decision process. Our experiments show that our approach leads to a better utilization of the assets and significantly improves the number of achievable missions when the number of available assets is limited.",

N2 - Some resources (i.e., assets) can be critical to accomplish missions. Unfortunately, in many settings these resources are limited. Scarcity of the critical assets and importance of the missions create an incentive for the organizations to cooperate by sharing their assets with an expectation of carrying out their missions successfully even if the assets in hand are limited. In this paper, we propose a multiagent framework where mission plans are semantically described so that a hierarchical multiagent system can be used to represent each mission. Using the semantic description of the mission plans, the agents reason about resources required for their missions and cooperatively decide on the assets that should be shared to carry out those missions. This is achieved at different levels of the agent hierarchy where policies and constraints are used during the decision process. Our experiments show that our approach leads to a better utilization of the assets and significantly improves the number of achievable missions when the number of available assets is limited.

AB - Some resources (i.e., assets) can be critical to accomplish missions. Unfortunately, in many settings these resources are limited. Scarcity of the critical assets and importance of the missions create an incentive for the organizations to cooperate by sharing their assets with an expectation of carrying out their missions successfully even if the assets in hand are limited. In this paper, we propose a multiagent framework where mission plans are semantically described so that a hierarchical multiagent system can be used to represent each mission. Using the semantic description of the mission plans, the agents reason about resources required for their missions and cooperatively decide on the assets that should be shared to carry out those missions. This is achieved at different levels of the agent hierarchy where policies and constraints are used during the decision process. Our experiments show that our approach leads to a better utilization of the assets and significantly improves the number of achievable missions when the number of available assets is limited.